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#DATA (baris = Merek Tablet, kolom = Pelarut)#
Y <- matrix(c(46.18, 54.54, 56.63,
              57.69, 71.57, 81.51,
              48.61, 51.01, 80.02),
            nrow=3, byrow=TRUE,
            dimnames=list(Merek_Tablet=c("CDR","Redoxon","Enervon-C"),
                          Jenis_Pelarut=c("Air Biasa","Air Soda","Air Kelapa")))
Y

##             Jenis_Pelarut
## Merek_Tablet Air Biasa Air Soda Air Kelapa
##    CDR           46.18    54.54      56.63
##    Redoxon       57.69    71.57      81.51
##    Enervon-C     48.61    51.01      80.02

#ANAVA 2 ARAH TANPA INTERAKSI#
anava2arah_tanpa <- function(Y, alpha=0.05){
  a <- nrow(Y)
  b <- ncol(Y)
  N <- a*b

  FK <- sum(Y)^2/N
  JKT <- sum(Y^2) - FK
  JK_A <- sum(rowSums(Y)^2)/b - FK
  JK_B <- sum(colSums(Y)^2)/a - FK
  JKG <- JKT - JK_A - JK_B

  db <- c(a-1, b-1, (a-1)*(b-1), N-1)
  JK <- c(JK_A, JK_B, JKG, JKT)
  KT <- JK/db
  F <- c(KT[1:2]/KT[3], NA, NA)
  Ft <- c(qf(1-alpha, db[1:2], db[3]), NA, NA)
  p <- c(pf(F[1:2], db[1:2], db[3], lower.tail=FALSE), NA, NA)

  hasil <- data.frame(Sumber=c("Merek Tablet","Jenis Pelarut","Galat","Total"),
  db, JK, KT, F_hit=F, F_tabel=Ft, p_value=p)
  print(hasil, digits=5, na.print="", row.names=FALSE)
}
anava2arah_tanpa(Y)

##         Sumber db      JK      KT  F_hit F_tabel  p_value
##   Merek Tablet  2  479.96 239.979 4.2696  6.9443 0.101762
##  Jenis Pelarut  2  733.92 366.960 6.5287  6.9443 0.054991
##          Galat  4  224.83  56.207     NA      NA       NA
##          Total  8 1438.70 179.838     NA      NA       NA

#PEMBANDING DENGAN FUNGSI BAWAAN R#
data <- as.data.frame(as.table(Y))
anova(aov(Freq ~ Merek_Tablet + Jenis_Pelarut, data=data))

## Analysis of Variance Table
## 
## Response: Freq
##               Df Sum Sq Mean Sq F value  Pr(>F)  
## Merek_Tablet   2 479.96  239.98  4.2696 0.10176  
## Jenis_Pelarut  2 733.92  366.96  6.5287 0.05499 .
## Residuals      4 224.83   56.21                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1